Agronomic biofortification increases grain zinc concentration of maize grown under contrasting soil types in Malawi

Abstract Zinc (Zn) deficiency remains a public health problem in Malawi, especially among poor and marginalized rural populations, linked with low dietary intake of Zn due to consumption of staple foods that are low in Zn content. The concentration of Zn in staple cereal grain can be increased through application of Zn‐enriched fertilizers, a process called agronomic biofortification or agro‐fortification. Field experiments were conducted at three Agricultural Research Station sites to assess the potential of agronomic biofortification to improve Zn concentration in maize grain in Malawi as described in registered report published previously. The hypotheses of the study were (i) that application of Zn‐enriched fertilizers would increase in the concentration of Zn in maize grain to benefit dietary requirements of Zn and (ii) that Zn concentration in maize grain and the effectiveness of agronomic biofortification would be different between soil types. At each site two different subsites were used, each corresponding to one of two agriculturally important soil types of Malawi, Lixisols and Vertisols. Within each subsite, three Zn fertilizer rates (1, 30, and 90 kg ha−1) were applied to experimental plots, using standard soil application methods, in a randomized complete block design. The experiment had 10 replicates at each of the three sites as informed by a power analysis from a pilot study, published in the registered report for this experiment, designed to detect a 10% increase in grain Zn concentration at 90 kg ha−1, relative to the concentration at 1 kg ha−1. At harvest, maize grain yield and Zn concentration in grain were measured, and Zn uptake by maize grain and Zn harvest index were calculated. At 30 kg ha−1, Zn fertilizer increased maize grain yields by 11% compared with nationally recommended application rate of 1 kg ha−1. Grain Zn concentration increased by 15% and uptake by 23% at the application rate of 30 kg ha−1 relative to the national recommendation rate. The effects of Zn fertilizer application rate on the response variables were not dependent on soil type. The current study demonstrates the importance of increasing the national recommendation rate of Zn fertilizer to improve maize yield and increase the Zn nutritional value of the staple crop.

three sites as informed by a power analysis from a pilot study, published in the registered report for this experiment, designed to detect a 10% increase in grain Zn concentration at 90 kg ha À1 , relative to the concentration at 1 kg ha À1 . At harvest, maize grain yield and Zn concentration in grain were measured, and Zn uptake by maize grain and Zn harvest index were calculated. At 30 kg ha À1 , Zn fertilizer increased maize grain yields by 11% compared with nationally recommended application rate of 1 kg ha À1 . Grain Zn concentration increased by 15% and uptake by 23% at the application rate of 30 kg ha À1 relative to the national recommendation rate.
The effects of Zn fertilizer application rate on the response variables were not dependent on soil type. The current study demonstrates the importance of increasing the national recommendation rate of Zn fertilizer to improve maize yield and increase the Zn nutritional value of the staple crop. Malawi with large prevalence rate among women and children (Gupta et al., 2020;Siyame et al., 2013). Recent studies estimate that 62% of the Malawian population is Zn-deficient (Likoswe et al., 2020;National Statistical Office [NSO], 2017), and this is likely to be larger in rural populations (Siyame et al., 2013;Tang et al., 2022). Zinc is an essential micronutrient which has important functions in all biological systems (Broadley et al., 2007). Its deficiency in humans is associated with multiple health problems that include immune system impairments, retarded physical growth and brain development among children under 5 years of age, and poor birth outcomes in women (Gibson, 2012;Krebs et al., 2014;Terrin et al., 2015). Various interventions, such as application of Zn-enriched fertilizers, are possible means of reducing Zn deficiency in humans through increasing the concentration of Zn in the edible parts of crops (Joy, Stein, et al., 2015;Liu et al., 2017;Manzeke et al., 2014;White & Broadley, 2009). Field experiments were designed, based on pilot study data, to explore how to increase the Zn nutritional quality of maize grain in Malawi through agronomic biofortification; the protocol was published as a registered report (Botoman et al., 2020). The results are presented in this paper.
The main aim of this study was to assess the potential of agronomic biofortification by soil application of Zn-enriched fertilizers to increase Zn concentration in the edible part of maize. Specifically, the study was conducted to: determine the extent to which the application of Zn-enriched fertilizers to soils increases the concentration of Zn in grains; to examine differences in grain Zn concentration between soil types; and to determine how the effectiveness of agronomic biofortification differs between soil types. If the experiment provides evidence for an effect of agronomic biofortification on concentration of Zn in maize grain, then in the short term, this intervention could be a cost-effective way to alleviate Zn deficiency among the rural population in Malawi.

| MATERIALS AND METHODS
The protocol for the experiment was reported previously in detail (Botoman et al., 2020) and a brief description is provided here.

| Materials
Maize was chosen as it is the principal staple cereal crop in Malawi.
The maize variety used in the experiment was an F 1 hybrid, SC

| Description of the experimental sites
The study was conducted at Chitala, Chitedze, and Ngabu Agricultural Research Stations in Lilongwe, Salima, and Chikwawa districts, respectively, during the 2019-2020 cropping season. Prior to starting the experiment, soil samples were collected from five points randomly spaced across the whole experimental area of each soil type at each site, at a depth of 0-20 cm. The collected soil samples were thoroughly mixed, and a 500-g composite sample was taken and analyzed for baseline soil characteristics (Table 1). Generally, the results show that the soils had a wide range of properties. Vertisols had larger mean values of pH, organic carbon, total nitrogen, and exchangeable bases across all sites, confirming that these soils are more fertile than Lixisols.

| Zn fertilizer treatments, experimental design and statistical analysis
Different Zn application rates of 1, 30, and 90 kg ha À1 of elemental Zn were applied at the three-leaf growth stage to all the plots at all sites. The gross plot size was five ridges, each 5 m long, with the net plot being the three middle ridges, each 3 m long. The ridges were spaced at 75 cm apart. All fertilizers were applied as a basal application by manually placing the fertilizers using the "spot" (or "dollop") method at 10 cm depth and 12.5 cm away from the planting station at a right angle to the ridge axis, as typically practiced by farmers. The use of 1 kg Zn ha À1 was based on national recommended application rates for Zn fertilizers in Malawi (Ministry of Agriculture and Food Security [MoAFS], 2016). The use of 30 and 90 kg Zn ha À1 fertilizer rates in the experiment was informed by low Zn grain concentration in the pilot trial, where a lower maximum Zn application rate of 20 kg ha À1 was used (Botoman et al., 2020).
The three Zn fertilizer rates were applied to the three plots allocated within 10 complete randomized blocks at each of the six subsites (one on a Lixisol and one on a Vertisol at each of the three sites).
The allocation of treatments to plots within blocks was done independently and at random using a script for the R platform (R Core Team, 2017). The choice of the number of blocks is critical to determine the sensitivity of the experiment to detect the true effect sizes of the fertilizer treatment, and because of this, we undertook a power analysis by simulation (Botoman et al., 2020).
Data analyses were conducted using the nlme package for the R platform (Pinheiro et al., 2021). A linear mixed model was used with a random effects structure to reflect how the fertilizer rate is randomized among plots within sets of blocks all within one subsite of a single soil type. A fixed effects model was used comprising main effects of fertilizer rate, soil type and their interaction. Further, the main effect of fertilizer rate was partitioned into linear and nonlinear components with an appropriate choice of orthogonal polynomials and similarly examined the partition of the soil-fertilizer interaction into components based on these two components of the fertilizer effect. The output of the analysis tested the specific hypotheses concerning differences between soil types and fertilizer application rates with respect to response variable, with confidence intervals, of the effects of Zn fertilizer application on response variable at the 30 and 90 kg Zn ha À1 relative to the recommended rate of 1 kg Zn ha À1 . After estimation of the model parameters histograms were plotted of the random effects estimates at each level, the marginal residuals were plotted against the fitted values (Figures S1-S4) and summary statistics (Tables S1-S4) were computed. These outputs were examined to evaluate the plausibility of the assumption of normally distributed errors with homogeneous variances. In the case of maize grain yields, grain Zn concentrations and uptake these assumptions were accepted. For Zn HI , these assumptions were not accepted and data were transformed using a natural log.

| Trial implementation, data collection, and sample laboratory analysis
Maize was sown in December 2019 and harvested in April 2020 at Chitala and Ngabu and in May 2020 at Chitedze. At harvest, grain and stover samples were collected, prepared, and analyzed for grain and stover Zn concentrations as described by Botoman et al. (2020). A Certified Reference Material (CRM; Wheat flour SRM 1567b, National Institute of Standards and Technology, Gaithersburg, MD, US; 11.61 mg kg À1 ) and 12 operational blank digestions were used to determine the accuracy of the analyses and the limit of detection (LOD) for quality control. The Zn elemental recovery for SRM 1567b was 93%. To assess the benefit of Zn fertilizer application on maize yield, dry weight of maize grain (kg) was recorded from the net plots. Similarly, dry weight of stover (kg) was recorded and used to calculate Zn uptake by the crop and harvest index measures. Zinc uptake by the crop refers to the amount of Zn in the crop that is required to complete its life cycle.
Zinc harvest index (Zn HI ) is a ratio between Zn accumulated in the grain to that accumulated in the grain and stover combined (Fageria, 2014), expressed as a percentage. Daily rainfall data (mm) were also recorded using rain gauges stationed in each of the research stations where the experiment was conducted; results are presented in Figure 1. Generally, rainfall was well distributed at Chitala, fairly distributed at Chitedze and poorly distributed at Ngabu. Further, the difference in absolute quantities of rainfall is also apparent. No additional irrigation was used, in keeping with general agricultural practice in Malawi.

| Measurements of the residual availability of zinc in soil
The residual benefit of soil applied Zn to subsequent crops for improved grain Zn nutritional quality has previously been noted (Boawn, 1974;Brennan & Bolland, 2007;Grewal & Graham, 1999;Mari et al., 2015). Given that large Zn application rates were used, a study on the residual benefit of Zn on subsequent maize crop was conducted. The maize crop was grown on the same plots and ridges without plowing or any added Zn. This information will be T A B L E 1 Initial soil characteristics of the experimental sites There was no further significant changes in yield when the Zn application rate was increased to 90 kg ha À1 .  Figure 2. There was no evidence for differences among the soil types (p = .739) or for an interaction of Zn application rate with soil type. Thus, over all sites there was no difference in mean yield of maize grain between the two soil types, nor was there any evidence that the yield response to Zn differed between the soil types, either in the linear effect (p = .727) or the nonlinear effect (p = .278).

| Effects of soil type and Zn fertilizer on maize grain Zn concentration and uptake
The grain Zn concentrations and uptake for each fertilizer treatment at all experimental sites are presented in Figure 5b,c. This is accompanied by the standard errors calculated for each treatment level.
Positive responses of grain Zn concentration and uptake to Zn application rate are apparent. Figures 3 and 4 show the mean grain Zn concentration and uptake, respectively, together with their standard errors for the three Zn fertilizer application rates as estimated in the LMM. Grain Zn concentration and uptake at 30 kg ha À1 were $4 mg kg À1 (15% higher than 1 kg ha À1 ) and $40 g ha À1 (23% higher than 1 kg ha À1 ), respectively, greater than at 1 kg ha À1 ; no further significant increases was observed when the Zn application was increased to 90 kg ha À1 . In addition, there were noticeable differences in grain Zn concentration and uptake between the sites (Figure 5b,c).
The ANOVA for maize grain Zn concentration and Zn grain uptake are presented in  Gashu et al., 2021). Table 3 also shows the variance components for each random effect which were assumed in the original power analysis (Botoman et al., 2020). Note that our estimates from the experimental data are of the same order of magnitude, suggesting that the approach of a power analysis based on estimates from pilot studies and survey data is a robust approach to the design of experiments of adequate power.

| Soil type and Zn fertilizer effects on Zn harvest index
The mean Zn harvest indices (Zn HI ), measures of Zn grain loading efficiency by each Zn treatment at all sites, are presented in Figure 5d, together with the standard errors estimated separately for each of these datasets. A LMM was used to analyze the effects of soil type, Zn treatment and their interaction on Zn HI , as described above. The outputs for testing normality of the residuals showed a skewed distribution and the response variable was transformed to natural logarithm prior to analysis. After the transformation, the residuals appeared consistent with the assumption of a normal distribution and homogeneity of variances ( Figure S4).
The mean Zn HI decreased from 40% to 30% among the soil types in response to the increase of Zn application rate from 1 to 30 kg ha À1 , and no effect was observed when the rate was further increased from 30 to 90 kg ha À1 (Figure 6). However, no statistical inference was made from the plot since soil type was not replicated within any experimental site. There are observed differences in Zn HI between the sites. For example, there was about 8% more Zn loaded in the grain at Ngabu than Chitala and Chitedze. The variations in Zn HI response between sites might be attributed to differences in soil physical and chemical charateristics (Table 1).
Soils at Ngabu have a higher fertility status than those at Chitala and Chitedze.
The ANOVA for natural log of Zn harvest index is shown in Zinc plays important physiological roles in maize and its deficiency can reduce grain yields by up to 10% (Joy, Stein, et al., 2015). Several studies report a positive response of maize grain yields to the application of Zn fertilizer (Manzeke et al., 2014;Palai et al., 2020;Stewart et al., 2021). For example, Liu et al. (2020)  F I G U R E 3 Mean grain Zn concentration at the three experimental sites in response to Zn fertilizer application during the 2019-2020 cropping season. The error bars show the standard error of the mean (AESEM).
F I G U R E 4 Mean grain Zn uptake at the three experimental sites in response to Zn fertilizer application during the 2019-2020 cropping season. The error bars show the standard error of the mean (AESEM).
fertilizer resulted in significant increases in maize grain yields. Soil application of Zn fertilizer of 30 kg ha À1 increased maize grain yields by 11% over the national recommended Zn fertilizer rate of 1 kg ha À1 .
The additional grain produced when Zn fertilizer rate was increased from 1 to 30 kg ha À1 was $660 kg ha À1 . This translates to a minimum annual benefit (minimum additional income for the farmer) of about MK30,000 ha À1 ($$40 ha À1 ) based on the cost of Zn fertilizer and return on yield. The cost of Zn fertilizer was calculated based on commercial price (MK960 kg À1 ) and estimated quantities of 135 and 4.5 kg for 30 and 1 kg ha À1 , respectively. The return on yield was calculated using the minimum government maize price of MK220 kg À1 and obtained maize yields at respective Zn fertilizer application rates.
This shows that some benefit is realized in the first year. However, the annual benefit might be higher than the estimated as the price of maize varies with location. Further, the benefit of Zn fertilizer application could increase from the second year due to residual benefit of Zn in soil (Boawn, 1974;Brennan & Bolland, 2007).
In Malawi, Zn fertilizer application to improve maize crop yields is recommended (MoAFS, 2016). The ability to add the Zn to the fertilizer blend already recommended by the Government of Malawi further means that this approach does not create additional labor or other time costs for farmers, compared with current practice. This may also incur a smaller price differential than purchase of Zn fertilizer. Some researchers have suggested that the increase in grain yield with the application of Zn fertilizer is due to increase in kernel density (Abunyewa & Mercie-Quarshie, 2004;Liu et al., 2020;Potarzycki, 2010 (Joy, Kumssa, et al., 2015;Joy, Stein, et al., 2015;Manary et al., 2002). The reported data further showed that the positive response of Zn fertilizer on grain Zn concentration and uptake did not depend on soil type. Based on the findings of the present study, an agronomic biofortification program of maize in Malawi might be implemented on these two soil types using a blanket Zn fertilizer application, without adjustment of the fertilizer application common practice used by farmers in the country, and leading to a more nutri-  (Curie et al., 2009;Palmer & Guerinot, 2009).

| CONCLUSION
The current study provides evidence of the effectiveness and effi-

CONFLICT OF INTEREST
The authors declare no competing interests.